{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/incrementality-testing"},"x-facet":{"type":"skill","slug":"incrementality-testing","display":"Incrementality Testing","count":5},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_87cfb794-843"},"title":"Data Scientist","description":"<p>Replit is redefining how software is built and who gets to build it. Our mission is Autonomy for All , making programming accessible, collaborative, and powered by AI.</p>\n<p>This role owns how Replit understands its customers across every touchpoint. You&#39;ll build the analytics and intelligence layer that spans marketing performance, customer signals, and support , turning massive volumes of behavioural data, feedback, and interaction signals into insights that drive growth, retention, and revenue.</p>\n<p>You will:</p>\n<ul>\n<li>Design and analyse marketing experiments across paid, lifecycle, and content channels; optimise CAC, LTV, and ROAS</li>\n<li>Build multi-touch attribution and marketing mix models to understand what&#39;s driving growth</li>\n<li>Synthesise customer signals , support tickets, social, reviews, CSAT , into automated intelligence that reaches the teams who need it</li>\n<li>Build churn and retention models to identify at-risk users and inform lifecycle intervention strategies</li>\n<li>Define and maintain customer segmentations and personas that drive targeting, messaging, and product decisions</li>\n<li>Build the analytical foundation for Voice of the Customer , connecting qualitative feedback signals to quantitative behaviour data at scale</li>\n<li>Detect emerging product issues and bugs faster by surfacing support signal early enough to shape engineering priorities</li>\n<li>Optimise automation and deflection to reduce support load and improve self-serve resolution rates</li>\n<li>Build the measurement foundation to fully optimise ROI across all support activities</li>\n<li>Use LLMs and agentic workflows to analyse unstructured data at scale and automate recurring analysis</li>\n<li>Create automated reporting that puts key metrics to inform the company</li>\n</ul>\n<p>Required Skills and Experience:</p>\n<ul>\n<li>6+ years of experience in data science with a focus on marketing, growth, or customer analytics</li>\n<li>Strong SQL skills and experience with large-scale event-level user behaviour data; 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In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p><strong>About the team</strong></p>\n<p>OpenAI’s mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Marketing team helps deeply understand customer audiences and market dynamics, influence the development of the right products, build sustainable and customer-aligned monetization models, and drive awareness, adoption, and usage across OpenAI’s products and platform.</p>\n<p><strong>About the role</strong></p>\n<p>We’re looking for an <strong>Advertising Marketing Science</strong> leader to establish and scale OpenAI’s advertiser-facing reporting, measurement, and attribution credibility. You’ll combine deep measurement expertise with strong judgment and cross-functional leadership to define how advertisers understand performance on OpenAI and how our reporting aligns with their existing measurement frameworks (MTA, incrementality/lift testing, MMM/geo experimentation).</p>\n<p>This role will start as a hands-on individual contributor responsible for building the methodological foundations of OpenAI’s advertising measurement system. Over time, you will define the strategy, operating model, and team needed to scale this function globally as advertiser adoption grows.</p>\n<p>This role is ideal for someone who enjoys building new capabilities from first principles, can translate complex causal measurement approaches into trusted industry narratives, and is energized by partnering across Product, Engineering, Sales, Partnerships and Legal to build a privacy-first measurement ecosystem.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li><strong>Define OpenAI’s advertiser measurement strategy</strong>, establishing how our reporting aligns with attribution (MTA), incrementality/lift testing, MMM, geo experimentation, and partner measurement frameworks.</li>\n</ul>\n<ul>\n<li><strong>Build the foundation of OpenAI’s Marketing Science function</strong>, initially leading work as an individual contributor while designing the long-term team structure, operating model, and measurement programs.</li>\n</ul>\n<ul>\n<li><strong>Lead advertiser-facing measurement discussions</strong>, representing OpenAI in executive briefings, measurement escalations, and industry conversations while building trust in our methodologies and reporting.</li>\n</ul>\n<ul>\n<li><strong>Develop clear advertiser narratives</strong> that translate causal inference, attribution models, and statistical methodologies into understandable guidance for campaign optimization and investment decisions.</li>\n</ul>\n<ul>\n<li><strong>Design and govern OpenAI’s advertising measurement program</strong>, including standardized experiment patterns (A/B, geo, quasi-experimental), power calculators, diagnostics, and experiment-quality guardrails.</li>\n</ul>\n<ul>\n<li><strong>Build scalable measurement frameworks</strong> that reconcile results across MMM, MTA, and lift testing, helping advertisers triangulate OpenAI performance within their broader marketing measurement systems.</li>\n</ul>\n<ul>\n<li><strong>Establish privacy-centric measurement approaches as needed</strong>, including aggregated measurement, and conversion modeling in partnership with Legal and Privacy teams.</li>\n</ul>\n<ul>\n<li><strong>Translate measurement strategy into product capabilities</strong>, partnering with Product and Engineering to operationalize methodologies into durable measurement tools and reporting infrastructure.</li>\n</ul>\n<ul>\n<li><strong>Shape OpenAI’s external measurement ecosystem</strong>, working with third-party measurement partners, clean-room providers, and industry groups to align standards and reduce friction for advertisers.</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have <strong>deep expertise in advertising measurement</strong> including experimentation, incrementality testing, attribution modeling, and econometric approaches such as MMM.</li>\n</ul>\n<ul>\n<li>Have <strong>experience designing and scaling lift or incrementality programs</strong>, including governance, experimentation frameworks, and statistical quality standards.</li>\n</ul>\n<ul>\n<li>Are comfortable acting as a <strong>senior external measurement authority</strong>, confidently leading advertiser conversations, navigating discrepancies, and building trust with sophisticated marketing organizations.</li>\n</ul>\n<ul>\n<li>Can <strong>translate complex statistical concepts into practical decision frameworks</strong> for both technical and non-technical audiences.</li>\n</ul>\n<ul>\n<li>Can <strong>build functions from the ground up</strong>, setting strategy while also executing hands-on during early stages of team development.</li>\n</ul>\n<ul>\n<li>Have successfully partnered with <strong>Product and Engineering teams to translate measurement science into scalable product capabilities</strong>.</li>\n</ul>\n<ul>\n<li>Have experience working with <strong>third-party measurement providers or industry standards organizations</strong>.</li>\n</ul>\n<ul>\n<li>Thrive in <strong>fast-paced, high-ambiguity environments</strong> and are comfortable leading cross-company initiatives without direct authority.</li>\n</ul>\n<ul>\n<li>Care deeply about building <strong>trusted, privacy-forward measurement systems</strong> that enable long-term advertiser confidence.</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.</p>\n<p>We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.</p>\n<p>For additional information, please see [OpenAI’s Affirm</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_c29dbc40-9e1","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/5547d275-f123-46e1-8695-71fd79a05724","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"Full time","x-salary-range":"$284K – $415K","x-skills-required":["Advertising measurement","Experimentation","Incrementality testing","Attribution modeling","Econometric approaches","Statistical quality standards","Measurement frameworks","Data analysis","Data visualization","Communication skills","Leadership skills","Collaboration skills"],"x-skills-preferred":["Data science","Machine learning","Statistics","Mathematics","Computer programming","Data engineering","Cloud computing","Big data","Data governance","Data security"],"datePosted":"2026-03-08T22:14:24.485Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Marketing","industry":"Technology","skills":"Advertising measurement, Experimentation, Incrementality testing, Attribution modeling, Econometric approaches, Statistical quality standards, Measurement frameworks, Data analysis, Data visualization, Communication skills, Leadership skills, Collaboration skills, Data science, Machine learning, Statistics, Mathematics, Computer programming, Data engineering, Cloud computing, Big data, Data governance, Data security","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":284000,"maxValue":415000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_39a574a0-94c"},"title":"Technical Program Manager, Marketing Technology","description":"<p>As a Technical Program Manager for Marketing Technology, you will lead our Marketing Mix Modeling (MMM), incrementality testing, brand measurement, and marketing data infrastructure programs. 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Establish operational excellence standards including monitoring, alerting, version control, automated privacy validation, and incident response protocols while maintaining executive visibility into platform initiatives and working with Legal and Security on vendor reviews.</li>\n<li><strong>Marketing Workflow Automation</strong>: Partner with Marketing leadership to identify, prioritize, and support deployment of AI-powered automation solutions for marketing operations. Establish governance frameworks, quality standards, validation processes, and monitoring mechanisms for automated marketing workflows. Build sustainable operating models for ongoing automation maintenance and continuous improvement. Track and measure automation impact to demonstrate ROI to leadership and cross-functional teams. 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high-intent prospects, optimise lead scoring, and improve targeting for paid acquisition campaigns.</li>\n<li>Partner with marketing, growth, and revenue teams to translate business questions into rigorous analysis and clear recommendations.</li>\n<li>Create self-service dashboards and automated reporting that surface key marketing metrics (CAC, LTV, ROAS, conversion rates) for go-to-market teams.</li>\n<li>Build and maintain data pipelines that integrate marketing platforms (Google Ads, Meta, Iterable, Segment, etc.) with our product analytics.</li>\n</ul>\n<p><strong>Examples of what you could do</strong></p>\n<ul>\n<li>Build propensity models to identify which free users are most likely to convert to plans based on usage patterns and engagement signals.</li>\n<li>Analyse cohort behaviour and retention patterns to optimise lifecycle marketing campaigns and reduce churn.</li>\n<li>Develop segmentation models to personalise messaging and targeting for different user personas (students, hobbyists, professional developers, enterprise teams).</li>\n<li>Build real-time alerting systems to flag anomalies in campaign performance or conversion metrics, automate bidding adjustments across platforms.</li>\n</ul>\n<p><strong>Required skills and experience</strong></p>\n<ul>\n<li>Bachelor&#39;s degree in Computer Science, Statistics, Mathematics, Economics, or related field, OR equivalent real-world experience in data roles.</li>\n<li>4+ years of experience in data science or related roles with a focus on marketing, growth, or business analytics.</li>\n<li>Strong SQL skills and experience working with large datasets, particularly event-level user behaviour data, and designing ETL workflows using dbt</li>\n<li>Proficiency in Python and data science libraries (pandas, scikit-learn, statsmodels, etc.).</li>\n<li>Experience designing and analysing A/B tests and experiments, including statistical rigor around sample sizing, significance testing, and causal inference.</li>\n<li>Experience building dashboards and visualisations (Looker, Tableau, Mode, or similar tools).</li>\n<li>Ability to translate ambiguous business questions into structured analysis and communicate findings clearly to non-technical stakeholders.</li>\n</ul>\n<p><strong>Preferred Qualifications</strong></p>\n<ul>\n<li>Experience with modern data stack (dbt, BigQuery, Snowflake, Fivetran, etc.).</li>\n<li>Background in growth analytics, marketing analytics, or conversion rate optimisation at a SaaS or PLG company.</li>\n<li>Familiarity with marketing technology platforms (Google Analytics, Segment, Iterable, Marketo, HubSpot, etc.).</li>\n<li>Experience with attribution modelling, marketing mix modelling, or incrementality testing.</li>\n<li>Understanding of PLG (product-led growth) motions and self-serve conversion funnels.</li>\n</ul>\n<p><strong>Bonus Points</strong></p>\n<ul>\n<li>Experience analysing freemium or usage-based pricing models.</li>\n<li>Understanding of developer tools, collaborative coding environments, or technical products.</li>\n<li>Experience with causal inference methods (difference-in-differences, synthetic control, propensity score matching).</li>\n<li>Familiarity with customer data platforms (CDPs) and event tracking implementation.</li>\n<li>Experience working with sales and customer success data to analyse expansion revenue and upsell opportunities.</li>\n</ul>\n<p><strong>Full-Time Employee Benefits Include</strong></p>\n<ul>\n<li>Competitive Salary &amp; Equity</li>\n<li>401(k) Program with a 4% match</li>\n<li>Health, Dental, Vision and Life Insurance</li>\n<li>Short Term and Long Term Disability</li>\n<li>Paid Parental, Medical, Caregiver Leave</li>\n<li>Commuter Benefits</li>\n<li>Monthly Wellness Stipend</li>\n<li>Autonomous Work Environment</li>\n<li>In Office Set-Up Reimbursement</li>\n<li>Flexible Time Off (FTO) + Holidays</li>\n<li>Quarterly Team Gatherings</li>\n<li>In Office Amenities</li>\n</ul>\n<p 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